Note that Chebyshev polynomial approximation makes \(g_\theta \)  \(K\) -localized and reduces its computational complexity from \(\mathcal {O}(n^2)\)  to \(\mathcal {O}(K|\mathcal {E}|)\) .
Therefore, Chebyshev Graph Convolutional operation can be effectively employed to capture the spatial correlations of the power grid data.
More details can be found in [1]}, [2]}.
